经过GPU训练的.pb模型不适用于只有CPU的机器

Question

我重新跟踪TensorFlow Inception-v3模型文件_图形.pb'通过使用GPU。在

我转了个再培训班_图形.pb'文件到AWS EC2 t2.micro服务器（ubuntu 16.04.2），它没有GPU。在

当我试着在推理脚本的标签下_图像.py'在我的EC2服务器上

import tensorflow as tf
import sys
from tensorflow.python.platform import gfile


# change this as you see fit
image_path = sys.argv[1]

# Read in the image_data
image_data = tf.gfile.FastGFile(image_path, 'rb').read()

# Loads label file, strips off carriage return
label_lines = [line.rstrip() for line
                   in tf.gfile.GFile('/home/ubuntu/tf_files/retrained_labels.txt')]

# Unpersists graph from file

with tf.gfile.FastGFile('./retrained_graph.pb', 'rb') as f:
    graph_def = tf.GraphDef()
    graph_def.ParseFromString(f.read())
    _ = tf.import_graph_def(graph_def, name='')
with tf.Session() as sess:
    # Feed the image_data as input to the graph and get first prediction
    softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')

    predictions = sess.run(softmax_tensor, \
             {'DecodeJpeg/contents:0': image_data})

    # Sort to show labels of first prediction in order of confidence
    top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]

    for node_id in top_k:
        human_string = label_lines[node_id]
        score = predictions[0][node_id]
        print('%s::%.5f::' % (human_string, score))

它不能处理这个错误

^{pr2}$

但是在另一个模型上的推理是经过训练的非gpu支持的，在同一个脚本的标签上可以很好地工作_图像.py'

如何在非GPU环境下运行此推理脚本？在